U.S. flag

An official website of the United States government

Dot gov

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Https

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

PubAg

Main content area

A comparative study between nonlinear regression and nonparametric approaches for modelling Phalaris paradoxa seedling emergence

Author:
J L Gonzalez‐Andujar, M Francisco‐Fernandez, R Cao, M Reyes, J M Urbano, F Forcella, F Bastida
Source:
Weed research 2016 v.56 no.5 pp. 367-376
ISSN:
0043-1737
Subject:
Phalaris paradoxa, cumulative distribution, data collection, microclimate, models, regression analysis, seedling emergence, weeds
Abstract:
Parametric nonlinear regression (PNR) models are used widely to fit weed seedling emergence patterns to soil microclimatic indices. However, such approximation has been questioned, mainly due to several statistical limitations. Alternatively, nonparametric approaches can be used to overcome the problems presented by PNR models. Here, we used an emergence data set of Phalaris paradoxa to compare both approaches. Mean squared error and correlation results indicated higher accuracy for the descriptive ability but similar poor performance for predictive ability of the nonparametric approach in comparison with the PNR approach. These results suggest that our nonparametric cumulative distribution function approach is a valuable alternative to the classical parametric nonlinear regression models to describe complex emergence patterns for P. paradoxa, but not to predict them.
Agid:
5497853
Handle:
10113/5497853